LG-CNN: From local parts to global discrimination for fine-grained recognition

By Guosen Xie, Xu-Yao Zhang, Wenhan Yang, Mingliang Xu, Shuicheng Yan, Chenglin Liu. 2017

66 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Ling Shao
2. Li Liu
3. Fan Zhu
4. Zheng Zhang
5. Jie Qin
6. Álvaro García-Martín
7. Marcos Escudero-Viñolo
8. Alejandro López-Cifuentes

Citations in the corpus

• Attentive Region Embedding Network for Zero-Shot Learning (2019, background): “In term of discriminative feature learning, the part based feature has long been established as a powerful one [12, 25].”
• Semantic-Aware Scene Recognition (2019, background): “[24] proposed to enhance fine-grained recognition by detecting part candidates based on saliency detection and by constructing a CNN architecture with local parts and global discrimination.”